of high volatility compared to periods of low volatility, using a regime-switching vector autoregression. The lower … that is weaker in high volatility periods. To rationalize our robust empirical results, we use a macroeconomic model in … volatility of aggregate shocks. In low volatility periods, banks lever up, which makes their balance sheets more sensitive to …

model and a stochastic volatility factor model, it is possible to estimate reliable uncertainty measures and describe their …

This paper proposes a multivariate stochastic volatility-in-vector autoregression model called the conditional … data so they are associated with changes in the volatility of the shocks hitting the macroeconomy. Second, we advance a new …

accounts for time variation in macroeconomic volatility, known as the great moderation. In particular, we consider an … volatility processes and mixture distributions for the irregular components and the common cycle disturbances enable us to … that time-varying volatility is only present in the a selection of idiosyncratic components while the coefficients driving …

This paper uses a FAVAR model with stochastic volatility to estimate the impact of uncertainty shocks on real income …

volatility as well as the U.S. economy. We find that - even after accounting for these factors - oil price uncertainty still has … confirms these results. Finally, significant spillover effects in the GARCH model suggest that oil price volatility is a gauge …